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Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software

BACKGROUND: There is an increasing need for computer-generated models that can be used for explaining the emergence and predicting the behavior of multi-protein dynamic structures in cells. Multi-agent systems (MAS) have been proposed as good candidates to achieve this goal. RESULTS: We have created...

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Autores principales: Soula, Hédi, Robardet, Céline, Perrin, François, Gripon, Sébastien, Beslon, Guillaume, Gandrillon, Olivier
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1242347/
https://www.ncbi.nlm.nih.gov/pubmed/16171521
http://dx.doi.org/10.1186/1471-2105-6-228
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author Soula, Hédi
Robardet, Céline
Perrin, François
Gripon, Sébastien
Beslon, Guillaume
Gandrillon, Olivier
author_facet Soula, Hédi
Robardet, Céline
Perrin, François
Gripon, Sébastien
Beslon, Guillaume
Gandrillon, Olivier
author_sort Soula, Hédi
collection PubMed
description BACKGROUND: There is an increasing need for computer-generated models that can be used for explaining the emergence and predicting the behavior of multi-protein dynamic structures in cells. Multi-agent systems (MAS) have been proposed as good candidates to achieve this goal. RESULTS: We have created 3DSpi, a multi-agent based software that we used to explore the generation of multi-protein dynamic structures. Being based on a very restricted set of parameters, it is perfectly suited for exploring the minimal set of rules needed to generate large multi-protein structures. It can therefore be used to test the hypothesis that such structures are formed and maintained by principles of self-organization. We observed that multi-protein structures emerge and that the system behavior is very robust, in terms of the number and size of the structures generated. Furthermore, the generated structures very closely mimic spatial organization of real life multi-protein structures. CONCLUSION: The behavior of 3DSpi confirms the considerable potential of MAS for modeling subcellular structures. It demonstrates that robust multi-protein structures can emerge using a restricted set of parameters and allows the exploration of the dynamics of such structures. A number of easy-to-implement modifications should make 3DSpi the virtual simulator of choice for scientists wishing to explore how topology interacts with time, to regulate the function of interacting proteins in living cells.
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spelling pubmed-12423472005-10-07 Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software Soula, Hédi Robardet, Céline Perrin, François Gripon, Sébastien Beslon, Guillaume Gandrillon, Olivier BMC Bioinformatics Software BACKGROUND: There is an increasing need for computer-generated models that can be used for explaining the emergence and predicting the behavior of multi-protein dynamic structures in cells. Multi-agent systems (MAS) have been proposed as good candidates to achieve this goal. RESULTS: We have created 3DSpi, a multi-agent based software that we used to explore the generation of multi-protein dynamic structures. Being based on a very restricted set of parameters, it is perfectly suited for exploring the minimal set of rules needed to generate large multi-protein structures. It can therefore be used to test the hypothesis that such structures are formed and maintained by principles of self-organization. We observed that multi-protein structures emerge and that the system behavior is very robust, in terms of the number and size of the structures generated. Furthermore, the generated structures very closely mimic spatial organization of real life multi-protein structures. CONCLUSION: The behavior of 3DSpi confirms the considerable potential of MAS for modeling subcellular structures. It demonstrates that robust multi-protein structures can emerge using a restricted set of parameters and allows the exploration of the dynamics of such structures. A number of easy-to-implement modifications should make 3DSpi the virtual simulator of choice for scientists wishing to explore how topology interacts with time, to regulate the function of interacting proteins in living cells. BioMed Central 2005-09-19 /pmc/articles/PMC1242347/ /pubmed/16171521 http://dx.doi.org/10.1186/1471-2105-6-228 Text en Copyright © 2005 Soula et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Soula, Hédi
Robardet, Céline
Perrin, François
Gripon, Sébastien
Beslon, Guillaume
Gandrillon, Olivier
Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software
title Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software
title_full Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software
title_fullStr Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software
title_full_unstemmed Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software
title_short Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software
title_sort modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3dspi, a multi-agent-based software
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1242347/
https://www.ncbi.nlm.nih.gov/pubmed/16171521
http://dx.doi.org/10.1186/1471-2105-6-228
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